MModelspectraIndependent AI Model Intelligence
Head-to-head · Updated 2026-09-08
Model Comparison · Head to Head

DeepSeek-V4-Pro vs MiniMax M3

DeepSeek-V4-Pro wins on Overall, Coding, Multimodal. Every numeric field is compared below, with a worked monthly-cost example and a pick rule for each use case.

VendorDeepSeek / MiniMax
Data fields15+ dimensions
Updated2026-09-08
Read~9 min
01

Verdict at a glance

Bottom line: Choose DeepSeek-V4-Pro when coding depth, long-context reliability, lower refusal matter most; choose MiniMax M3 when its stronger dimensions is the priority.

Choose DeepSeek-V4-Pro if you…

  • Strongest open source
  • Value champion
  • Excellent math reasoning
  • Extremely low price
  • Best for: Coding, Math reasoning, Open-source deployment

Choose MiniMax M3 if you…

  • Strong agent ability
  • Open source
  • Low price
  • Best for: AI agents, Open source, Chinese
02

Head-to-head aggregate scores

Scores are 0–100, aggregated from public benchmark information and independently weighted across three leaderboards. Rank is out of 22 tracked models.

DeepSeek-V4-Pro Higher overall
DeepSeek · #8 overall
Overall77
Coding79
Multimodal77
VS
MiniMax M3
MiniMax · #13 overall
Overall70
Coding68
Multimodal70

Aggregated from public sources and independently weighted; methodology on the Terms page. Scores within 3 points are treated as statistically tied.

03

Specs & pricing — every field side by side

List API prices in USD per 1M tokens. The highlighted cell is the stronger value/capability on that row.

DimensionDeepSeek-V4-ProMiniMax M3Verdict
VendorDeepSeek (CN)MiniMax (CN)Different vendors
Released2026.042026.06MiniMax M3 is newer
Overall (rank)77 · #870 · #13DeepSeek-V4-Pro +7
Coding79 · #568 · #13DeepSeek-V4-Pro +11
Multimodal77 · #1370 · #18DeepSeek-V4-Pro +7
Context window1M1MTie
Max output128K64KMiniMax M3 longer
Effective-context9490DeepSeek-V4-Pro more reliable
Input $/1M$0.44$0.6DeepSeek-V4-Pro cheaper
Output $/1M$1.32$2.4DeepSeek-V4-Pro cheaper
Cache discountnonenoneTie
Speed~70 tok/s~60 tok/sDeepSeek-V4-Pro faster
TTFT0.5s0.5sTie
Function calling8284MiniMax M3 ahead
Refusal rate~5%~7%DeepSeek-V4-Pro less restrictive
English8270DeepSeek-V4-Pro
Chinese8588MiniMax M3
ModalitiestexttextSame
Open weightsYesYesBoth open
Fine-tuningYesYes
Free tierDeepSeek App free; new API users receive creditsHailuo AI free; open-platform quota
SOC2 / no-trainno / yesno / yes
Private deploymentYesYesBoth support it

Fields drawn from vendor public documentation and the Modelspectra 22-model dataset; speed varies with network, concurrency and prompt length. Verify current pricing before purchase.

04

Dimension-by-dimension analysis

Reasoning & overall intelligence

DeepSeek-V4-Pro leads the overall aggregate by 7 points (77 vs 70). That is a meaningful, not marginal, edge on hard, multi-step reasoning, while MiniMax M3 remains a strong generalist that is not out of its depth on routine work.

Agentic coding

This is a clear gap: DeepSeek-V4-Pro scores 79 against 68. On multi-file edits, SWE-style tickets and long-horizon agent loops DeepSeek-V4-Pro needs fewer correction turns; MiniMax M3 is still competent for scripts and assisted completion but trails as task complexity rises.

Multimodal

DeepSeek-V4-Pro leads multimodal 77 vs 70. Neither emits native video, so the comparison is about parsing images and documents, not generation.

Speed & latency

DeepSeek-V4-Pro is faster in interactive use: ~70 tok/s with 0.5s TTFT versus ~60 tok/s with 0.5s TTFT (about 1.2× the throughput). For conversational UIs where perceived responsiveness drives retention, that edge is a real product factor even when raw reasoning is lower.

Context: window vs usable recall

Nominal windows are 1M for DeepSeek-V4-Pro and 1M for MiniMax M3. Effective-context scores point the same way as window size — DeepSeek-V4-Pro is ahead on usable recall (94 vs 90), so prefer it for long-document work where details cannot be missed.

Price & total cost

DeepSeek-V4-Pro is the cheaper API at $0.44/$1.32 versus MiniMax M3 at $0.6/$2.4 per 1M input/output tokens — list input is about 1.4× lower.

Chinese vs English

English: DeepSeek-V4-Pro 82 vs MiniMax M3 70. Chinese: 85 vs 88. For Chinese-language production, MiniMax M3 is the stronger pick. Note that non-Chinese models generally require overseas network access for their APIs.

Tool use & ecosystem

Function-calling score: DeepSeek-V4-Pro 82 vs MiniMax M3 84, so MiniMax M3 has the edge on structured tool use. Fine-tuning is available from DeepSeek-V4-Pro and MiniMax M3. Factor in existing SDK/plugin familiarity — switching cost often outweighs a few-point tool-use gap.

05

Cost worked example — same workload, real token math

Assume a production workload of 100M input + 30M output tokens per month, with 90% of input tokens served from cache. Figures use public list prices.

Scenario · per monthDeepSeek-V4-ProMiniMax M3Gap
List priceno cache applied$84100M in × $0.44  +  30M out × $1.32$132100M in × $0.6  +  30M out × $2.41.57×gap
With caching90% of inputs cache-hit$84no published cache discount$132no published cache discount1.57×gap

Illustrative model; your input/output mix and cache-hit ratio change the result. Prices are list rates before any enterprise agreement.

06

Decision tree

IF the workload is agentic or multi-file coding and a wrong first pass is expensive  →  choose DeepSeek-V4-Pro (coding 79 vs 68).
IF you serve real-time users and latency is a product KPI  →  choose DeepSeek-V4-Pro (~70 tok/s, 0.5s TTFT).
IF you are cost-driven at scale on routine, high-volume workloads  →  choose DeepSeek-V4-Pro ($$0.44/$$1.32 per 1M in/out).
IF long-document recall has to be near-perfect  →  choose DeepSeek-V4-Pro (effective context 94 vs 90).
07

Frequently asked questions

How do costs compare at 100M tokens/month with caching?
At 100M input + 30M output with 90% of inputs cache-hit, DeepSeek-V4-Pro is about $84/month and MiniMax M3 about $132/month after cache discounts ($84 and $132 at list).
Does the bigger context window actually matter?
Nominal windows are DeepSeek-V4-Pro (1M) and MiniMax M3 (1M), but usable recall follows the effective-context score (94 vs 90). Prefer the higher effective-context model for long-document work where nothing can be missed.
What is the single-line recommendation?
Choose DeepSeek-V4-Pro for Coding, Math reasoning; choose MiniMax M3 for AI agents, Open source.
How quickly do these rankings change?
Modelspectra refreshes the aggregate as new public benchmarks and prices appear. Treat scores within 3 points as a tie and re-check before a committed purchase.